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The link between public support and private r&d effort: what is the optimal subsidy?

Author

Listed:
  • Néstor Duch-Brown

    () (Universitat de Barcelona & IEB)

  • José García-Quevedo

    () (Universitat de Barcelona & IEB)

  • Daniel Montolio

    () (Universitat de Barcelona & IEB)

Abstract

The effectiveness of R&D subsidies can vary substantially depending on their characteristics. Specifically, the amount and intensity of such subsidies are crucial issues in the design of public schemes supporting private R&D. Public agencies determine the intensities of R&D subsidies for firms in line with their eligibility criteria, although assessing the effects of R&D projects accurately is far from straightforward. The main aim of this paper is to examine whether there is an optimal intensity for R&D subsidies through an analysis of their impact on private R&D effort. We examine the decisions of a public agency to grant subsidies taking into account not only the characteristics of the firms but also, as few previous studies have done to date, those of the R&D projects. In determining the optimal subsidy we use both parametric and non-parametric techniques. The results show a non-linear relationship between the percentage of subsidy received and the firms’ R&D effort. These results have implications for technology policy, particularly for the design of R&D subsidies that ensure enhanced effectiveness.

Suggested Citation

  • Néstor Duch-Brown & José García-Quevedo & Daniel Montolio, 2011. "The link between public support and private r&d effort: what is the optimal subsidy?," Working Papers 2011/12, Institut d'Economia de Barcelona (IEB).
  • Handle: RePEc:ieb:wpaper:2011/6/doc2011-12
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    References listed on IDEAS

    as
    1. Hardle, Wolfgang & Linton, Oliver, 1986. "Applied nonparametric methods," Handbook of Econometrics,in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 38, pages 2295-2339 Elsevier.
    2. Xulia González & Jordi Jaumandreu & Consuelo Pazo, 2005. "Barriers to Innovation and Subsidy Effectiveness," RAND Journal of Economics, The RAND Corporation, vol. 36(4), pages 930-949, Winter.
    3. Chang-Yang Lee, 2002. "A simple model of R&D: An extension of the Dorfman-Steiner theorem," Applied Economics Letters, Taylor & Francis Journals, vol. 9(7), pages 449-452.
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    Citations

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    Cited by:

    1. Giovanni Cerulli & Bianca Poti', 2016. "Explaining firm sensitivity to R&D subsidies within a dose-response model: The role of financial constraints, real cost of investment, and strategic value of R&D," DEM Working Papers 2016/09, Department of Economics and Management.
    2. Catalina Bolancé & Zuhair Bahraoui & Ramon Alemany, 2015. "Estimating extreme value cumulative distribution functions using bias-corrected kernel approaches," Working Papers XREAP2015-01, Xarxa de Referència en Economia Aplicada (XREAP), revised Jan 2015.
    3. Anna Castañer & Mª Mercè Claramunt, 2014. "Optimal stop-loss reinsurance: a dependence analysis," Working Papers XREAP2014-04, Xarxa de Referència en Economia Aplicada (XREAP), revised Apr 2014.
    4. Simon Wiederhold, 2012. "The Role of Public Procurement in Innovation: Theory and Empirical Evidence," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 43.
    5. Esther Vayá & José Ramón García & Joaquim Murillo & Javier Romaní & Jordi Suriñach, 2016. "Economic impact of cruise activity: the port of Barcelona," Working Papers XREAP2016-07, Xarxa de Referència en Economia Aplicada (XREAP), revised Dec 2016.
    6. Michel Dumont, 2013. "Working Paper 01-13 - The impact of subsidies and fiscal incentives on corporate R&D expenditures in Belgium (2001-2009)," Working Papers 1301, Federal Planning Bureau, Belgium.
    7. Mercedes Ayuso & Montserrat Guillén & Jens Perch Nielsen, 2016. "Improving automobile insurance ratemaking using telematics: incorporating mileage and driver behaviour data," Working Papers XREAP2016-08, Xarxa de Referència en Economia Aplicada (XREAP), revised Dec 2016.
    8. Anna Castañer & Mª Mercè Claramunt & Alba Tadeo & Javier Varea, 2016. "Modelización de la dependencia del número de siniestros. Aplicación a Solvencia II," Working Papers XREAP2016-01, Xarxa de Referència en Economia Aplicada (XREAP), revised Sep 2016.

    More about this item

    Keywords

    R&D; public subsidies; evaluation;

    JEL classification:

    • O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy
    • H32 - Public Economics - - Fiscal Policies and Behavior of Economic Agents - - - Firm

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